So if you want to start a startup one day, what should you do in college? There are only two things you need initially: an idea and cofounders. And the m.o. for getting both is the same. Which leads to our sixth and last counterintuitive point: that the way to get startup ideas is not to try to think of startup ideas.

I've written a whole essay on this, so I won't repeat it all here. But the short version is that if you make a conscious effort to think of startup ideas, the ideas you come up with will not merely be bad, but bad and plausible-sounding, meaning you'll waste a lot of time on them before realizing they're bad.

The way to come up with good startup ideas is to take a step back. Instead of making a conscious effort to think of startup ideas, turn your mind into the type that startup ideas form in without any conscious effort. In fact, so unconsciously that you don't even realize at first that they're startup ideas.

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Quite long but plenty of amazing advice in here from the founders of Looker (acquired by Google)

“My biggest piece of advice to early-stage founders on fundraising is don't try to raise money too early,” says Tabb. “I see so many founders out there trying to raise with just an idea on a slide. We waited almost a year to raise money, until we knew it was a venture business — not every startup is, and you don’t want to get locked in. We were cranking along with customers and revenue. And it wasn’t all nailed down, but we had figured out enough of how go-to-market might work to know that it was workable. That made our seed raise in the summer of 2012 so much easier. If you build value, it takes the fundraising process from how good you are at pitching yourself to a place where you can simply say ‘Ask the people who are using us for their opinion about it.’”

As the investor on the receiving end of that fundraising tactic, Trenchard agrees that it was effective. “When we were deciding whether or not to invest in their seed round, Lloyd sent me a list of 10 customer references — many of them were First Round-backed companies. I talked to each and every one during diligence, and I was blown away. The love they had for the products was off the charts, they would have been very disappointed without it,” says Trenchard.

Learning a new language. “I created LookML to serve as the basis of our platform. It’s an abstraction layer, the sequel to SQL. My thought was that if we could simplify the problems with SQL and evolve the data language, it would be easier to use,” says Tabb. But banking on data analysts learning a new language was anything but a surefire move. “This was a scary one,” says Porterfield. “I remember those early existential questions: ‘Can analysts learn this language? Will they want to?’ Looking back now, it seems more obvious that developer-style tooling and workflows would be embraced. These days, there’s a lot of discussion that any time you can provide tools that increase someone’s leverage, they will adopt them. But that wasn’t clear at the time.”

“For most companies in the data space, pre-sales folks are like plumbers, they're just hooking stuff together. We tried to take a different approach at Looker by asking prospects for a dataset and then putting economics or math majors to work. In the early days, they wore all the hats: They were pre-sales, post-sales, customer support. Eventually, those became separate roles as we scaled,” says Bien.

“In the early days, Margaret had a habit of saying ‘We'll be successful when we have 1,000 true fans.’ That was our driving force — figuring out how to build a fanbase in enterprise software,” says Tabb. “If you make a product that customers love, your customers will love you back. It may seem cheesy, but it was really about love — that’s the emotion we wanted to evoke in our customers. We call customer success our ‘Department of Customer Love.’ We made ‘Love Looker Love’ one of our values. I had early customers tell me that life at their company was now divided into two eras: ‘Before Looker’ and ‘After Looker.’ That’s the reaction we were always chasing,” he says.

“Back in my college days, I was really into the ideas of Robert Greenleaf, who kicked off the concept of servant leadership. Today, as a CEO, that philosophy carries forward — I view myself as a steward,” says Bien. “My role is to remove obstacles for other people and remove ownership for myself.”

All startups say they’re ambitious. You better be if you take venture funding!

Stripe’s insight was that tackling ambitious problems doesn’t just make the potential prize bigger. Ambitious efforts are often more feasible than smaller ones, because the strongest people want to work on the most ambitious efforts. In our experience this positive talent effect was stronger than the negative effect of problem difficulty. So, paradoxically, tackling a bigger problem could be both more rewarding for the company and in a sense more tractable.

This probably needs to be qualified. Stripe is set up so that we’re successful when our customers are successful (in real, economic terms). Ambitious problems for Stripe look like enabling more internet businesses and supporting entrepreneurs in more countries, not getting more ad clicks. The talent effect of ambition certainly applies to Stripe-style problems, but I’m not sure if it’d work for something like ads.

Again all startups say “our team is our most important asset”; leaders say “the hardest part of my job is hiring good people”. But what most companies actually do day-to-day on recruiting is disastrous: generic job ads, clueless outside recruiters, screening on brand name, candidate-hostile interview processes, slow response times, etc. The poor recruiting results of most companies reflect the work they put in.

Stripe was different in two respects: effort and thoughtfulness.

In terms of effort, Stripe’s recruiting was absolutely relentless. On the front of the pipeline this meant investing in potential candidates that wouldn’t apply for years, through genuine 1:1 relationships as well as many small events that introduce Stripe and its team. Once candidates were active, Stripe tried to move very quickly. Ideally we'd turn around recruiting steps on the same day: respond to the candidates inbound email the same day, and even decide on and give them an offer on the same day as their interviews. We could close candidates before Google replied to their initial emails.

Stripe was also thoughtful in recruiting processes. This signaled to candidates that the company was clueful and understood the candidate’s perspective. One example is Stripe’s capture the flag program, which not only put Stripe on the radar of a lot of candidates, but also gave them a sense of the strength of the engineering team. Another example was Stripe’s guidance on what to expect for interviews. We’d send candidates a PDF describing exactly how their interviews would be conducted, how they’d be evaluated, and how to prepare. These certainly helped candidates present their best work in the interviews. But they also showed that Stripe actually cares about this, which candidates knew from experience many other companies did not.

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The importance of self-compassion in tempering the brittleness of self-efficacy

The main reason is that most people’s risk tolerance is very low, because self-efficacy (defined as “a person’s conviction or confidence about his or her abilities to mobilize the motivation, cognitive resources or courses of action needed to successfully execute a specific task within a given context”) is remarkably fragile. When it comes to trying and learning new things, people have difficulty transferring success in one arena to even highly related ones. Even small failures lead to learned helplessness so quickly, we learn to protect against that eventuality by not trying new things unless success is guaranteed.

The primary risk of entrepreneurship and other free agent lifestyles is not financial or even social — it is the risk to a person’s very self-concept as someone who does what they set out to do.

What we need if we want to change behavior at this fundamental level is to replace predictive models of behavior change—do this and you’ll get that —with exploratory models.

Stories may actually be a more accurate way of describing how people think about and use mental models of behavior change. Stories, like emergent systems, only move in one direction. They cannot be rolled back and played again. This irreproducibility suggests the importance of another form of psychological capital that is also highly correlated with successful behavior change: self-compassion. They are two sides to the same coin — you need self-efficacy to believe you can do it, but you equally need self-compassion to be ok when you don’t. Self-compassion aids change by removing the veil of shame and pain that keeps you from examining the causes of your mistakes (and often, leads you to indulge in the very same bad habit as a way of forgetting the pain). Self-forgiveness is the first step in fostering an invitational attitude that is open to feedback and learning, from yourself and others.

There is something about the turning of this coin — between efficacy and compassion — that I believe lies at the heart of the experimentation framework I’m envisioning. And the more I think about it, the more I suspect compassion is the far more radical and important side.

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Properly defined, a startup is the largest group of people you can convince of a plan to build a different future. A new company’s most important strength is new thinking: even more important than nimbleness, small size affords space to think.

If your product requires advertising or salespeople to sell it, it’s not good enough: technology is primarily about product development, not distribution. Bubble-era advertising was obviously wasteful, so the only sustainable growth is viral growth.

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I published the Level manifesto with great fanfare: The War on Developer Productivity (And How I Intend to Win It).

Quite a fascinating and interesting way to kick-off such endeavor. This can act as a major source of encouragement for giving one's 100% to the purpose. Of course, avoiding the risks of over-committing without periodic self-examination.

It seems like these two words sum up this last week pretty well for a majority of the group. There has been a lot of information to take in, within a short amount of time. Although it has been a bit on the chaotic side here and there, most of the class can agree that the more we see, the more fascinating it becomes. I think everyone is looking forward to attaining more clarity for the program as a whole. The enthusiasm is contagious. It seems the whole process is new for everyone, and everyone is excited for the adventure.

The capacity and willingness to develop, organize and manage a business venture along with any of its risks in order to make a profit. The most obvious example of entrepreneurship is the starting of new businesses.

Institutions are incubators of inventions... ? In my professional journey thus far I find the startup landscape to be more actively catalyzing invention and propelling change through society. That is, unless, more universities have programs like CU-Boulder's? Their invention & entrepreneurship initiative is cross-campus and cross- department: https://www.colorado.edu/researchinnovation/ I would love to read a report similar to this one that focuses on trends in higher ed institutions when it comes to being incubators of inventions and entrepreneurship more broadly... who is doing that work and reporting?

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Embracing an Entrepreneurial Culture on Campus go.nmc.org/uni(Tom Corr, University Affairs, 4 May 2016.) The Ontario Network of Entrepreneurs is gaining global recognition for its efforts to bolster students’ business skills through investing in multiple campus events and programs. For example, the success of Ontario Centres of Excellence has led to the establishment of similar innovation hubs throughout North America, the UK, Australia, and Asia.

What’s fascinating here is that the province might be cutting a major part of the funding for the Ontario Centres of Excellence, particularly the part which has to do with Entrepreneurship Programs.
(My current work is associated with Lead To Win, a Campus-Linked Accelerator out of Carleton University.)

stack fallacy - Tech companies often fail when they create a new product by building upward from their existing product. They may know the technology well -- but fail to do enough research about what customers want. It is easier to innovate downward, by developing a product that you need yourself.